Machine Learning, Big Data, and IoT for Medical Informatics

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics, emphasizing their usability in handling structured and unstructured data and privacy preservation techniques. It is a valuable resource for scientists, researchers, practitioners, and academicians working in intelligent medical informatics and can be used as a reference book for undergraduate and graduate courses.

Format: Paperback / softback
Length: 458 pages
Publication date: 16 June 2021
Publisher: Elsevier Science Publishing Co Inc

Machine Learning, Big Data, and IoT for Medical Informatics delves into the cutting-edge techniques employed in the realm of medical informatics. These techniques, including machine learning, big data, and IoT, hold immense importance in disease diagnosis and prediction. In the field of medicine, the intricate structure of data becomes crucial for accurate predictive analytics, especially when dealing with diverse data types like ECG data, X-ray images, and image data. Recognizing this, this book emphasizes the usability of machine learning, big data, and IoT-based techniques in handling structured and unstructured data. Furthermore, it sheds light on the critical aspect of privacy preservation in medical data. Serving as a comprehensive reference book, this volume caters to scientists, researchers, practitioners, and academicians engaged in the field of intelligent medical informatics. Additionally, it serves as a valuable resource for undergraduate and graduate courses, such as medical informatics, machine learning, big data, and IoT.

Weight: 938g
Dimension: 190 x 236 x 30 (mm)
ISBN-13: 9780128217771